Qwen2 72B vs Qwen2.5 72B: Benchmark Comparison
Detailed comparison of Qwen2 72B and Qwen2.5 72B covering benchmarks, pricing, context window, and compliance.
Key Specifications
| Specification | Qwen2 72B | Qwen2.5 72B |
|---|---|---|
| Vendor | alibaba | alibaba |
| Version | 2-72b | 2.5-72b |
| Release Date | 2024-06-07 | 2024-09-19 |
| Context Window | 131072 tokens | 131072 tokens |
| Input Modalities | text | text |
| Output Modalities | text | text |
| License | Qwen License | Qwen License |
| SOC2 | ✗ | ✗ |
| HIPAA | ✗ | ✗ |
| GDPR | ✗ | ✗ |
| ISO 27001 | ✗ | ✗ |
Benchmark Results
| Benchmark | Qwen2 72B | Qwen2.5 72B | Winner |
|---|---|---|---|
| ARC | 94.4 | — | Qwen2 72B |
| BBH | 83.4 | 82.4 | Qwen2 72B |
| GPQA | 53.6 | — | Qwen2 72B |
| GSM8K | 87 | 88.4 | Qwen2.5 72B |
| HUMANEVAL | 76.5 | 86.6 | Qwen2.5 72B |
| IFEVAL | 76.9 | — | Qwen2 72B |
| MATH | 71.9 | 83.1 | Qwen2.5 72B |
| MMLU | 80.2 | 86.1 | Qwen2.5 72B |
| MUSR | 68.9 | — | Qwen2 72B |
| WINOGRANDE | 82.5 | — | Qwen2 72B |
Pricing Comparison
| Tier (per Mtok) | Qwen2 72B | Qwen2.5 72B |
|---|---|---|
| Input | $0.5 | $0.5 |
| Output | $0.8 | $0.8 |
| Cache Read | $0 | $0 |
| Cache Write | $0 | $0 |
Qwen2 72B 대 Qwen2.5 72B
모델 개요
Qwen2 72B and Qwen2.5 72B are both notable options in the AI model market. This page compares their benchmarks, pricing, and compliance.
핵심 사양
| 공급업체 | 출시일 | 컨텍스트 창 | 라이선스 |
|---|---|---|---|
| Alibaba / Alibaba | 2024-06-07 / 2024-09-19 | 131K / 131K | Qwen License / Qwen License |
벤치마크 성능
| 벤치마크 | Qwen2 72B | Qwen2.5 72B | 승자 |
|---|---|---|---|
| ARC | 94.4 | — | A |
| BBH (BIG-Bench Hard) | 83.4 | 82.4 | A |
| GPQA | 53.6 | — | A |
| GSM8K (Grade School Math 8K) | 87.0 | 88.4 | B |
| HumanEval | 76.5 | 86.6 | B |
| IFEval | 76.9 | — | A |
| MATH | 71.9 | 83.1 | B |
| MMLU (Massive Multitask Language Understanding) | 80.2 | 86.1 | B |
| MUSR | 68.9 | — | A |
| WinoGrande | 82.5 | — | A |
가격 비교
| 입력 | 출력 | 캐시 읽기 | 캐시 쓰기 |
|---|---|---|---|
| — / — | — / — | — / — | — / — |
백만 토큰당 — A / B
강점 & 약점
Qwen2 72B
- ✅ MMLU score 80.2, strong knowledge reasoning.
- ✅ GSM8K 87.0, robust math reasoning.
- ⚠️ 闭源专有模型，不支持自托管。
Qwen2.5 72B
- ✅ MMLU score 86.1, strong knowledge reasoning.
- ✅ HumanEval 86.6, excellent code generation.
- ✅ GSM8K 88.4, robust math reasoning.
- ⚠️ 闭源专有模型，不支持自托管。
편집자 의견
Qwen2 72B and Qwen2.5 72B each have their strengths. Choose based on workload (code, long context, vision), referencing the tables above.
FAQ
Which model is better for coding tasks?
Refer to the HumanEval benchmark table; the model with a higher score is better suited for coding tasks.
Which model is cheaper?
Refer to the pricing comparison table above; the model with lower input/output prices is more cost-effective.
Which has a longer context window?
Refer to the key specifications table; the model with a larger context window is better for long documents.
참고문헌
Editor's Take
See Editor's Take section.